Triple
T23623269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nukhayb |
E583379
|
entity |
| Predicate | countryBorderFunction |
P153313
|
FINISHED |
| Object | transit point for pilgrims traveling between Iraq and Saudi Arabia |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: transit point for pilgrims traveling between Iraq and Saudi Arabia | Statement: [Nukhayb, countryBorderFunction, transit point for pilgrims traveling between Iraq and Saudi Arabia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryBorderFunction Context triple: [Nukhayb, countryBorderFunction, transit point for pilgrims traveling between Iraq and Saudi Arabia]
-
A.
countyBorder
Indicates that two counties share a common boundary or border with each other.
-
B.
countryBorderType
Indicates the type or nature of the border relationship that exists between two countries.
-
C.
countryBorderFeatureOf
Indicates that a geographical feature (such as a river, mountain range, or coastline) serves as or is part of the border of a country.
-
D.
countryBorderRelation
Indicates that two countries share a common land or maritime boundary with each other.
-
E.
provinceBordering
Indicates that two provinces share a common boundary or border with each other.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e248fc8d74819091bd5baef2f36f6f |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b17ae58c8190b7b6cdc57c6ead3a |
completed | April 29, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69f118d0e0588190a86527a7747c5427 |
completed | April 28, 2026, 8:30 p.m. |
| PDg | Predicate description generation | batch_69f138b8c9248190b059bc38a9a50958 |
completed | April 28, 2026, 10:46 p.m. |
Created at: April 17, 2026, 6:46 p.m.